HDFR: A Hydrologic Data and Modeling System with On-Demand Access to Environmental Sensing Data for Decision Making

Abstract

This paper introduces the Hydrologic Disaster Forecasting and Response (HDFR), an online data and modeling integration software system that facilitates the machine-to-machine access to and the management of environmental sensing data from space and ground products. Available data sources include in-situ measurements from weather and hydrographic stations; remote sensing products from Doppler precipitation radars in the United States, Earth-monitoring satellites that measure precipitation, soil moisture, and snow cover; and numerical weather prediction model outputs from the U.S. National Weather Service. Additionally, the HDFR system provides a suite of hydrologic modeling tools; including data fusion, storm severity assessment, and hydrologic model preprocessing for the Distributed Hydrology Soil Vegetation Model (DHSVM); that are seamlessly incorporated with the diverse suite of data products. Two example workflows demonstrate how this unified framework could help bridge the gap between the online and on-demand accessing of growing wealth of Earth-observing data and hydrologic prediction for scientific and engineering applications.